datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
DatasetWithCapitalLettersdrlc-leaderboard-datadataset-with-standalone-yamlThis is a test dataset used in the datasets library CI
CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/huggingface/CADS-dataset.Dataset-GB1-fitness
Description
This dataset contains fitness score of mutant GB1 protein.
Protein Format: AA sequence
Splits
traing: 119644
valid: 14917
test: 14800
Related paper
Nicholas C Wu, Lei Dai, C Anders Olson, James O Lloyd-Smith, Ren Sun (2016) Adaptation in protein fitness landscapes is facilitated by indirect paths eLife 5:e16965
https://doi.org/10.7554/eLife.16965
Label
Label is the fitness of mutant protein. The fitness of each variant can be viewed as… See the full description on the dataset page: https://huggingface.co/datasets/SaProtHub/Dataset-GB1-fitness.Bitext-customer-support-llm-chatbot-training-dataset
Bitext - Customer Service Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the Customer Support sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-customer-support-llm-chatbot-training-dataset.officeqa
OfficeQA
Dataset Summary
OfficeQA is a grounded reasoning benchmark by Databricks for evaluating model and agent performance on end-to-end reasoning over real-world documents.
The benchmark consists of question–answer pairs that require reasoning over historical U.S. Treasury Bulletin documents (1939–2025), which contain dense financial tables, charts, and narrative text. OfficeQA is designed to test retrieval, tool use, and multi-step reasoning in… See the full description on the dataset page: https://huggingface.co/datasets/databricks/officeqa.TACK_Tunnel_Data
TACK Tunnel Data (TTD): A Benchmark Dataset for Deep Learning-Based Defect Detection in Tunnels
Tunnels are essential elements of transportation infrastructure, but are increasingly affected by ageing and deterioration mechanisms such as cracking. Regular inspections are required to ensure their safety, yet traditional manual procedures are time-consuming, subjective, and costly. Recent advances in mobile mapping systems and Deep Learning (DL) enable automated visual inspections.… See the full description on the dataset page: https://huggingface.co/datasets/TACK-project/TACK_Tunnel_Data.data_jobs
🧠 data_jobs Dataset
A dataset of real-world data analytics job postings from 2023, collected and processed by Luke Barousse.
Background
I've been collecting data on data job postings since 2022. I've been using a bot to scrape the data from Google, which come from a variety of sources.
You can find the full dataset at my app datanerd.tech.
Serpapi has kindly supported my work by providing me access to their API. Tell them I sent you and get 20% off paid plans.… See the full description on the dataset page: https://huggingface.co/datasets/lukebarousse/data_jobs.CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/4141ms/CADS-dataset.Obstacle-Detection-Dataset-YOLO
ROD-Dataset: Real-Time Obstacle Detection for Smartphone-Based Assistive Vision
24,326-image, 25-class YOLO dataset for obstacle detection
This dataset is the data product of our Real-Time Obstacle Detection (ROD) project at Amirkabir University of Technology, Tehran. The project addresses two related public-safety problems on the city sidewalk: the limited situational awareness of people living with visual impairments, and the elevated collision and fall risk for pedestrians… See the full description on the dataset page: https://huggingface.co/datasets/Abtinzandi/Obstacle-Detection-Dataset-YOLO.ai-model-popularity
Datamata AI Model Popularity Index
Weekly popularity of the most-downloaded and trending Hugging Face models: trailing downloads, likes, the model's task and its trending rank. One row per model from the most recent weekly snapshot.
Latest snapshot: 2026-10-04
Models in this release: 50
Updated: weekly
Licence: CC BY 4.0 — free to use and adapt, including commercially, with attribution.
Source & methodology: https://www.datamatastudios.com/datasets
Quickstart… See the full description on the dataset page: https://huggingface.co/datasets/datamatastudios/ai-model-popularity.spotify-tracks-dataset
Content
This is a dataset of Spotify tracks over a range of 125 different genres. Each track has some audio features associated with it. The data is in CSV format which is tabular and can be loaded quickly.
Usage
The dataset can be used for:
Building a Recommendation System based on some user input or preference
Classification purposes based on audio features and available genres
Any other application that you can think of. Feel free to discuss!
Column… See the full description on the dataset page: https://huggingface.co/datasets/maharshipandya/spotify-tracks-dataset.MVU-Eval-Data
MVU-Eval Dataset
Paper | Code | Project Page
Dataset Description
The advent of Multimodal Large Language Models (MLLMs) has expanded AI capabilities to visual modalities, yet existing evaluation benchmarks remain limited to single-video understanding, overlooking the critical need for multi-video understanding in real-world scenarios (e.g., sports analytics and autonomous driving). To address this significant gap, we introduce MVU-Eval, the first comprehensive benchmark… See the full description on the dataset page: https://huggingface.co/datasets/MVU-Eval-Team/MVU-Eval-Data.CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/arekborucki/CADS-dataset.doc-formats-csv-1
[doc] formats - csv - 1
This dataset contains one csv file at the root:
data.csv
kind,sound
dog,woof
cat,meow
pokemon,pika
human,hello
The YAML section of the README does not contain anything related to loading the data (only the size category metadata):
---
size_categories:
- n<1K
---
CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT… See the full description on the dataset page: https://huggingface.co/datasets/mrmrx/CADS-dataset.CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/WY-0206/CADS-dataset.eccv2026-cad-challenge-data
ECCV 2026 CAD Challenge Data
This challenge is part of the workshop The Path to Manufacturing: Evolving
3D Generation to Intelligent Computer-Aided Design.
Workshop homepage: https://3dgen-cad-workshop.github.io/
Challenge submission Space: https://huggingface.co/spaces/jingwei-xu-00/eccv2026-cad-challenge
Dataset rendering and preparation code (only .step files are required): https://github.com/DavidXu-JJ/eccv2026-cad-challenge-data-render
This repository contains the public… See the full description on the dataset page: https://huggingface.co/datasets/jingwei-xu-00/eccv2026-cad-challenge-data.hnm-fashion-recommendations-data
Dataset Rekomendasi Fashion H&M
Dataset ini berisi data transaksi, atribut pelanggan, dan metadata produk yang telah dianonimkan dari H&M Group. Kumpulan data komprehensif ini memungkinkan pemodelan perilaku pembelian pelanggan secara mendalam.
Wawasan yang dihasilkan dapat dimanfaatkan untuk berbagai tujuan bisnis yang strategis, mulai dari meningkatkan personalisasi pengalaman berbelanja, mengoptimalkan manajemen inventaris untuk efisiensi produksi, hingga mendukung inisiatif… See the full description on the dataset page: https://huggingface.co/datasets/einrafh/hnm-fashion-recommendations-data.ReactiveGWM-Datasets
ReactiveGWM-Datasets: Strategy-Aligned Rollouts for Reactive Game World Models
📚 Datasets-Introduction
ReactiveGWM-Datasets is the strategy-aligned training corpus that powers
ReactiveGWM, a game world
model that decouples player control from NPC autonomy. To learn that
decoupling, the model needs supervision that pairs each gameplay clip with
both a per-frame action stream (what the player did) and a high-level
NPC description (what the NPC tried to do, and under… See the full description on the dataset page: https://huggingface.co/datasets/INV-WZQ/ReactiveGWM-Datasets.Bitext-retail-ecommerce-llm-chatbot-training-dataset
Bitext - Retail (eCommerce) Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [Retail (eCommerce)] sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-retail-ecommerce-llm-chatbot-training-dataset.ICPC_Data
ICPC World Finals — a discriminative subset, with model traces
24 ICPC World Finals problems (2021–2025), together with 1440 full contest transcripts
of an LLM attempting them under simulated contest rules across three arms: with no hint,
with the official editorial as a hint, and with a hint written by a second model that gets
10 rounds of measured feedback to improve it.
Selection
The agent
Every contest run in this dataset comes from:… See the full description on the dataset page: https://huggingface.co/datasets/xupy21/ICPC_Data.CADS-dataset
CADS: A Comprehensive Anatomical Dataset and Segmentation for Whole-Body Anatomy in Computed Tomography
Overview
CADS is a robust, fully automated framework for segmenting 167 anatomical structures in Computed Tomography (CT), spanning from head to knee regions across diverse anatomical systems.
The framework consists of two main components:
CADS-dataset:
22,022 CT volumes with complete annotations for 167 anatomical structures.
Most extensive whole-body CT dataset… See the full description on the dataset page: https://huggingface.co/datasets/sunghong/CADS-dataset.Bitext-events-ticketing-llm-chatbot-training-dataset
Bitext - Events and Ticketing Tagged Training Dataset for LLM-based Virtual Assistants
Overview
This hybrid synthetic dataset is designed to be used to fine-tune Large Language Models such as GPT, Mistral and OpenELM, and has been generated using our NLP/NLG technology and our automated Data Labeling (DAL) tools. The goal is to demonstrate how Verticalization/Domain Adaptation for the [events and ticketing] sector can be easily achieved using our two-step approach to LLM… See the full description on the dataset page: https://huggingface.co/datasets/bitext/Bitext-events-ticketing-llm-chatbot-training-dataset.predictive-stock-datasetprotein_data_testsplit 1, 2 -> for sequences
split 3, 4 -> for residues
phishing-email-dataset
Phishing Email Dataset
This dataset on Hugging Face is a direct copy of the 'Phishing Email Detection' dataset from Kaggle, shared under the GNU Lesser General Public License 3.0. The dataset was originally created by the user 'Cyber Cop' on Kaggle. For complete details, including licensing and usage information, please visit the original Kaggle page.
skin-cancer-ham10000-datasetexercise-dataset
Exercise Dataset — Free Tier (RepDB)
A free, ready-to-use fitness exercise dataset: 609 exercises, each
illustrated with flat-style 512×512 WebP images (a start/peak pose pair, or
a single main pose for static holds and stretches), with target muscles,
equipment, MET values, and full instructions in English, German, and
Spanish.
This public snapshot is the free tier of RepDB. Free for personal
and commercial use inside applications, with attribution.
Need exercise… See the full description on the dataset page: https://huggingface.co/datasets/RepDB/exercise-dataset.